Multiuser MIMO-OFDM for Next-Generation Wireless Systems

This overview portrays the 40-year evolution of orthogonal frequency division multiplexing (OFDM) research. The amelioration of powerful multicarrier OFDM arrangements with multiple-input multiple-output (MIMO) systems has numerous benefits, which are detailed in this treatise. We continue by highlighting the limitations of conventional detection and channel estimation techniques designed for multiuser MIMO OFDM systems in the so-called rank-deficient scenarios, where the number of users supported or the number of transmit antennas employed exceeds the number of receiver antennas. This is often encountered in practice, unless we limit the number of users granted access in the base station’s or radio port’s coverage area. Following a historical perspective on the associated design problems and their state-of-the-art solutions, the second half of this treatise details a range of classic multiuser detectors (MUDs) designed for MIMO-OFDM systems and characterizes their achievable performance. A further section aims for identifying novel cutting-edge genetic algorithm (GA)-aided detector solutions, which have found numerous applications in wireless communications in recent years. In an effort to stimulate the cross pollination of ideas across the machine learning, optimization, signal processing, and wireless communications research communities, we will review the broadly applicable principles of various GA-assisted optimization techniques, which were recently proposed also for employment inmultiuser MIMO OFDM. In order to stimulate new research, we demonstrate that the family of GA-aided MUDs is capable of achieving a near-optimum performance at the cost of a significantly lower computational complexity than that imposed by their optimum maximum-likelihood (ML) MUD aided counterparts. The paper is concluded by outlining a range of future research options that may find their way into next-generation wireless systems

Channel estimation and signal enhancement for DS-CDMA systems

This dissertation focuses on topics of Bayesian-based multiuser detection, space-time (S-T) transceiver design, and S-T channel parameter estimation for direct-sequence code-division multiple-access (DS-CDMA) systems. Using the Bayesian framework, various linear and simplified nonlinear multiuser detectors are proposed, and their performances are analyzed. The simplified non-linear Bayesian solutions can bridge the performance gap between sub-optimal linear multiuser detectors and the optimum multiuser detector. To further improve the system capacity and performance, S-T transceiver design approaches with complexity constraint are investigated. Novel S-T receivers of low-complexity that jointly use the temporal code-signature and the spatial signature are proposed. Our solutions, which lead to generalized near-far resistant S-T RAKE receivers, achieve better interference suppression than the existing S-T RAKE receivers. From transmitter side, we also proposed a transmit diversity (TD) technique in combination with differential detection for the DS-CDMA systems. It is shown that the proposed S-T TD scheme in combination with minimum variance distortionless response transceiver (STTD+MVDR) is near-far resistant and outperforms the conventional STTD and matched filter based (STTD+MF) transceiver scheme. Obtaining channel state information (CSI) is instrumental to optimum S-T transceiver design in wireless systems. Another major focus of this dissertation is to estimate the S-T channel parameters. We proposed an asymptotic, joint maximum likelihood (ML) method of estimating multipath channel parameters for DS-CDMA systems. An iterative estimator is proposed to further simplify the computation. Analytical and simulation results show that the iterative estimation scheme is near-far resistant for both time delays and DOAs. And it reaches the corresponding CRBs after a few iterations

Interference suppression and diversity for CDMA systems

In code-division multiple-access (CDMA) systems, due to non-orthogonality of the spreading codes and multipath channels, the desired signal suffers interference from other users. Signal fading due to multipath propagation is another source of impairment in wireless CDMA systems, often severely impacting performance. In this dissertation, reduced-rank minimum mean square error (MMSE) receiver and reduced-rank minimum variance receiver are investigated to suppress interference; transmit diversity is applied to multicarrier CDMA (MC-CDMA) systems to combat fading; packet combing is studied to provide both interference suppression and diversity for CDMA random access systems. The reduced-rank MMSE receiver that uses a reduced-rank estimated covariance matrix is studied to improve the performance of MMSE receiver in CDMA systems. It is shown that the reduced-rank MMSE receiver has much better performance than the full-rank MMSE receiver when the covariance matrix is estimated by using a finite number of data samples and the desired signal is in a low dimensional subspace. It is also demonstrated that the reduced-rank minimum variance receiver outperforms the full-rank minimum variance receiver. The probability density function of the output SNR of the full-rank and reduced-rank linear MMSE estimators is derived for a general linear signal model under the assumption that the signals and noise are Gaussian distributed. Space-time coding that is originally proposed for narrow band systems is applied to an MC-CDMA system in order to get transmit diversity for such a wideband system. Some techniques to jointly decode the space-time code and suppress interference are developed. The channel estimation using either pilot channels or pilot symbols is studied for MC-CDMA systems with space-time coding. Performance of CDMA random access systems with packet combining in fading channels is analyzed. By combining the current retransmitted packet with all its previous transmitted copies, the receiver obtains a diversity gain plus an increased interference and noise suppression gain. Therefore, the bit error rate dramatically decreases with the number of transmissions increasing, which in turn improves the system throughput and reduces the average delay

Turbo receivers for interleave-division multiple-access systems

In this paper several turbo receivers for Interleave-Division Multiple-Access (IDMA) systems will be discussed. The multiple access system model is presented first. The optimal, Maximum A Posteriori (MAP) algorithm, is then presented. It will be shown that the use of a precoding technique at the emitter side is applicable to IDMA systems. Several low complexity Multi-User Detector (MUD), based on the Gaussian approximation, will be next discussed. It will be shown that the MUD with Probabilistic Data Association (PDA) algorithm provides faster convergence of the turbo receiver. The discussed turbo receivers will be evaluated by means of Bit Error Rate (BER) simulations and EXtrinsic Information Transfer (EXIT) charts

A joint-channel diagonalization for multiuser MIMO antenna systems

In this paper, we address the problem of improving the performance of multiuser space-division multiplexing (SDM) systems where multiple independent signal streams can be transmitted in the same frequency and time slot. The problem is important in multiuser multiple-input multiple-output systems where communication from one base station to many mobile stations can occur simultaneously. Our objective is to devise a multiuser linear space-time precoder for simultaneous channel diagonalization of the multiuser channels enabling SDM. Our new approach is based on diagonalizing the multiuser channel matrices and we use a variation of successive Jacobi rotations. In addition to the diagonalization, our approach attempts to optimize the resultant channel gains for performance enhancement. Our method is valid for both frequency-flat and frequency-selective fading channels but we assume that the base station knows all the channels and that they are quasi-stationary

Cyclic Prefix-Free MC-CDMA Arrayed MIMO Communication Systems

The objective of this thesis is to investigate MC-CDMA MIMO systems where the antenna array geometry is taken into consideration. In most MC-CDMA systems, cyclic pre xes, which reduce the spectral e¢ ciency, are used. In order to improve the spectral efficiency, this research study is focused on cyclic pre x- free MC-CDMA MIMO architectures. Initially, space-time wireless channel models are developed by considering the spatio-temporal mechanisms of the radio channel, such as multipath propaga- tion. The spatio-temporal channel models are based on the concept of the array manifold vector, which enables the parametric modelling of the channel. The array manifold vector is extended to the multi-carrier space-time array (MC-STAR) manifold matrix which enables the use of spatio-temporal signal processing techniques. Based on the modelling, a new cyclic pre x-free MC- CDMA arrayed MIMO communication system is proposed and its performance is compared with a representative existing system. Furthermore, a MUSIC-type algorithm is then developed for the estimation of the channel parameters of the received signal. This proposed cyclic pre x-free MC-CDMA arrayed MIMO system is then extended to consider the effects of spatial diffusion in the wireless channel. Spatial diffusion is an important channel impairment which is often ignored and the failure to consider such effects leads to less than satisfactory performance. A subspace-based approach is proposed for the estimation of the channel parameters and spatial spread and reception of the desired signal. Finally, the problem of joint optimization of the transmit and receive beam- forming weights in the downlink of a cyclic pre x-free MC-CDMA arrayed MIMO communication system is investigated. A subcarrier-cooperative approach is used for the transmit beamforming so that there is greater flexibility in the allocation of channel symbols. The resulting optimization problem, with a per-antenna transmit power constraint, is solved by the Lagrange multiplier method and an iterative algorithm is proposed